一类具有退偿增长曲线的生物种群的捕获优化问题

本文研究一类具有延偿增长曲线的生物种群,讨论了该种群的动力学性质及捕获问题,确定了最优捕获努力量、相应的种群密度和最大可持续捕获量、讨论了开放条件下的生物资源的管理。     

广义Logistic模型的捕获优化问题

以王寿松所提出的广义Ｌｏｇｉｓｔｉｃ模型为基础,讨论单种群生物资源的捕获优化问题,分析了被开发生物种群的动力学性质。在单位捕获努力量假定下,以最大可持续捕获量为管理目标,确定了线性捕获下的最优捕获策略,得到了最优捕获努力量,最大可持续收获及相应的最优种群水平的显式表达式,包括著名的Ｓｃｈａｅｆｅｒ模型作为特例,推广了相应的结果。     

山楂叶螨种群空间格局及其应用的研究Ⅱ．成螨种群密度综合估计及其抽样技术

本文结合Ｉｗａｏ零频率法和Ｇｅｒｒａｒｄ阈限密度法,提出一种改进的种群密度估计方法──“综合阈限密度估计法”,并由此探讨了苹果树上山楂叶螨成螨的密度估计及其抽样技术．采用零样频率来估计成螨的平均密度,并得到用概率保证的理论抽样数模型．比较结果表明,零频率法所需的理论抽样数少于直接计数法．综合阈限密度估计法的拟合效果更为显著．     

寄生蜂种群繁殖分布时间特征的研究

运用１０种寄生蜂的２３张生殖力表资料,分析比较了这些种群繁殖分布的特征．结果表明,寄生蜂种群繁殖具有相似的分布特征,种群繁殖集中分布在生殖头ｄ天内,在生殖头ｄ／２天内繁殖分布更为集中．在生殖头ｄ天内种群繁殖对种群增长的贡献几乎均达到１００％,其中大部分贡献是在生殖头ｄ／２天内实现的．这种繁殖分布特征对于寄生蜂种群内禀增长率的测定和掌握种群数量动态的时间特性十分重要．本文结合Ｉｗａｏ零频率法和Ｇｅｒｒａｒｄ阈限密度法,提出一种改进的种群密度估计方法──“综合阈限密度估计法”,并由此探讨了苹果树上山楂叶螨成螨的密度估计及其抽样技术．采用零样频率来估计成螨的平均密度,并得到用概率保证的理论抽样数模型．比较结果表明,零频率法所需的理论抽样数少于直接计数法．综合阈限密度估计法的拟合效果更为显著．     

红外相机技术在陕西观音山自然保护区兽类监测研究中的应用

国外使用红外相机技术开展野生动物调查研究已有较长的历史,最早的报道见于Champion(1927),在20世纪90年代逐渐发展成熟,广泛用于动物种群数量和密度的研究.如应用红外相机和种群捕获模型(Capture-recapture)对印度Nagarahole国家公园的孟加拉虎(Panthera tigris)的种群数量和密度的研究(Karanth,1995;Karanth和Nichols;1998),验证了红外相机技术与种群捕获模型的结合在孟加拉虎种群预测方面的优势,有效解决了监测中孟加拉虎数量稀少、活动隐秘等问题.     

基因捕获技术及其最新进展

基因捕获技术是目前最具应用前景的基因克隆方法之一。利用该技术建立的随机插入突变的突变体文库,可用于寻找、鉴定和研究大量末知功能和已知功能的活化基因,它是继自然突变、物理突变和化学突变之后发展起来的新的分子生物学方法。基因捕获载体是带有报告基因和/或选择标记基因的不完整的基因表达载体;这些载体所带的基因只有在整合到宿主功能基因内部且与融合的宿主基因编码框一致时才能得以表达。经典的基因捕获载体有：增强子捕获载体、基因捕获载体和启动子捕获载体。增强子载体只有一个最小化的启动子控制下游报告基因的表达活性。只有当启动子上游存在一个增强子时才能启动其下游基因的转录：而单独依靠这个启动了则不能转录。狭义的基因捕获载体是指插入到结构基因内部从而捕获该基因的载体,分为内含子捕获载体和外显了捕获载体。前者插入内含子,因此需要在无启动子的报告基因前面添加一个splice acceptor（SA）位点：后者插入外显子,因此不需SA位点就能产生融合蛋白mRNA。启动子捕获载体由一个无启动子的报告基因和选择标记基因组成,只有在捕状载体捕入到内源基因的外显子中,且两阅读框一致的时候才会有报告基因和被捕获的内源基因上游编码区的融合蛋白的表达。利用某些遗传元件的遗传特性也可以构建非常有用的捕获载体。常用的有：逆转录病毒介导的捕抉载体和转座子介导的捕荻载体等等。该文较为全面地概括了转座子介导的捕获载体的用途和研究现状。比如：在拟南芥中应用Ac／Ds转座子元件,存果蝇中应用P-element和piggyBac转座元件,在斑马鱼中应用T012转座了元件,在脊椎动物研究中应用Tc1/meriner转座了超家族,以及存哺乳动物和小鼠ES细胞中应用piggyBac转座子元件。还列举了设计新颖的载体优化策略,比如：发展新的选择标记基因,利用内源核糖体识别／结合位点（IRES）,去掉起始密码子和加一小段接头（1inker）等方法。最后介绍了几种针特定实验目的而设计的捕获载体。附录部分还列出了关于基因捕获技术的网络资源。     

高山姬鼠种群数量动态及预测预报模型

为了摸清高山姬鼠种群数量变节变动规律,探讨其种群数量预测方法,采用夹夜法调查逐月捕获率,用捕获率为预测指标,建立种群数量预测预报模型。对1996-2008年贵州省大方县高山姬鼠种群数量动态及种群数量进行分析预测,结果表明:高山姬鼠主要分布于稻田、旱地耕作区,是大方县农田害鼠优势种,占总鼠数的62.32%。10a平均捕获率为(2.58±1.27)%,全年种群数量变动曲线呈单峰型,各年度种群数量的变化曲线基本相似,一年内种群数量在6月份出现1个数量高峰,平均捕获率达(4.63±3.03)%。不同年度、不同月份、不同季节之间种群数量存在显著差异。根据历年高山姬鼠种群数量变动幅度及发生危害情况,结合当地鼠害防治指标,制定了高山姬鼠种群数量分级标准。分析1996-2008年高山姬鼠数量高峰期前各月捕获率、种群繁殖参数(性比、怀孕率、胎仔数、睾丸下降率、繁殖指数)与数量高峰期6月种群密度的关系后发现,4月份种群数量基数与6月份种群密度之间相关极显著,运用回归分析方法,建立了应用4月份种群数量基数(X)预测数量高峰期6月份种群密度(Y)的短期预测预报模型:Y=1.7558X+0.1442,可提前2个月预测当年数量峰种群密度和发生程度,经回测验证,数值和数量级预测值与实测值基本相符,数值预测和数量级预测平均吻合率为92.84%、100.00%,结果比较准确,故该预测预报模型具有一定的实用性和可行性。     

稻纵卷叶螟幼虫的空间分布型与抽样技术

害虫预测预报和防治的技术基础之一是对害虫种群动态的全面了解,其中种群数量在空间和时间上的变动是害虫种群动态的基本形式。怎样才能准确地掌握害虫种群数量的变动呢?最科学和简便的方法是作田间虫口密度的调查。田间调查是采用抽样技术非全面地估计害虫种群数量,但是抽样技术的应用受多种因素的制约,特别是受害虫种群内部个体空间分布型的影响较大,影响样本估计值的正确程度,     

田间昆虫的取样调查技术

田间昆虫取样调查技术直接关系到昆虫种群数量估计以及预测预报的准确性。田间取样调查结果的有效性由调查时抽样方法、抽样数和样本采集方法选取的科学合理性所决定。抽样方法有随机抽样、分层抽样、多重抽样、选择性抽样和顺序抽样。抽样方法的选择需根据昆虫种群的空间分布及作物类型而定。抽样数的多少由要求的调查结果的准确程度及调查种群数量的变异程度所决定。现有的昆虫样本的采集方法较多,主要有直接目测法、振落法、扫网法、吸虫器法和诱集法等。样本采集方法的选择要遵循"调查结果准确、操作简单方便和工作量小"的原则。总之,田间昆虫种群的取样调查,既要保证调查结果的准确性,也要保证调查时间和花费的经济性。     

棉田牧草盲蝽三种种群密度调查方法的比较分析

【目的】寻求科学、准确、有效的棉田牧草盲蝽Lygus pratensis(Linnaeus)发生规律和种群密度的调查方法,为棉田牧草盲蝽的预测预报、防治提供理论依据和指导。【方法】采用整体目测法、局部目测法、扫网法3种方法调查了棉田牧草盲蝽的种群数量并进行比较分析。【结果】(1)对牧草盲蝽种群动态,扫网法相较于整体目测法和局部目测法成虫有两个发生高峰期且发生初期提前1周;整体目测法和局部目测法较扫网法若虫初发期和高峰期均提前1周左右,局部目测法和整体目测法若虫发生趋势基本一致。(2)不同调查方法牧草盲蝽种群密度存在显著性差异,整体目测法获得的若虫及成虫和若虫种群密度均显著高于扫网法和局部目测法;2015年扫网法和整体目测法间的成虫种群密度差异不显著,均显著高于局部目测法,2016年扫网法成虫种群密度显著高于整体目测法。【结论】扫网法能够准确反应牧草盲蝽成虫的发生情况,整体目测法则适合若虫的种群调查,建议实际调查中使用整体目测和扫网相结合的方法,能为该虫预测预报和防治提供准确的依据和指导。     

Density estimation in live-trapping studies

Unbiased estimation of population density is a major and unsolved problem in animal trapping studies. This paper describes a new and general method for estimating density from closed-population capture–recapture data. Many estimators exist for the size (N) and mean capture probability ( p ) of a closed population. These statistics suffer from an unknown bias due to edge effect that varies with trap layout and home range size. The mean distance between successive captures of an individual (     ) provides information on the scale of individual movements, but is itself a function of trap spacing and grid size. Our aim is to define and estimate parameters that do not depend on the trap layout. In the new method, simulation and inverse prediction are used to estimate jointly the population density (D) and two parameters of individual capture probability, magnitude (g₀) and spatial scale (σ), from the information in     , p and     . The method uses any configuration of traps (e.g. grid, web or line) and any choice of closed-population estimator. It is assumed that home ranges have a stationary distribution in two dimensions, and that capture events may be simulated as the outcome of competing Poisson processes in time. The method is applied to simulated and field data. The estimator appears unusually robust and free from bias.     

Predator Presence and Vegetation Density Affect Capture Rates and Detectability of Litoria aurea Tadpoles: Wide-Ranging Implications for a Common Survey Technique

Trapping is a common sampling technique used to estimate fundamental population metrics of animal species such as abundance, survival and distribution. However, capture success for any trapping method can be heavily influenced by individuals’ behavioural plasticity, which in turn affects the accuracy of any population estimates derived from the data. Funnel trapping is one of the most common methods for sampling aquatic vertebrates, although, apart from fish studies, almost nothing is known about the effects of behavioural plasticity on trapping success. We used a full factorial experiment to investigate the effects that two common environmental parameters (predator presence and vegetation density) have on the trapping success of tadpoles. We estimated that the odds of tadpoles being captured in traps was 4.3 times higher when predators were absent compared to present and 2.1 times higher when vegetation density was high compared to low, using odds ratios based on fitted model means. The odds of tadpoles being detected in traps were also 2.9 times higher in predator-free environments. These results indicate that common environmental factors can trigger behavioural plasticity in tadpoles that biases trapping success. We issue a warning to researchers and surveyors that trapping biases may be commonplace when conducting surveys such as these, and urge caution in interpreting data without consideration of important environmental factors present in the study system. Left unconsidered, trapping biases in capture success have the potential to lead to incorrect interpretations of data sets, and misdirection of limited resources for managing species.     

Genetic sampling for estimating density of common species

Understanding population dynamics requires reliable estimates of population density, yet this basic information is often surprisingly difficult to obtain. With rare or difficult‐to‐capture species, genetic surveys from noninvasive collection of hair or scat has proved cost‐efficient for estimating densities. Here, we explored whether noninvasive genetic sampling (NGS) also offers promise for sampling a relatively common species, the snowshoe hare (Lepus americanus Erxleben, 1777), in comparison with traditional live trapping. We optimized a protocol for single‐session NGS sampling of hares. We compared spatial capture–recapture population estimates from live trapping to estimates derived from NGS, and assessed NGS costs. NGS provided population estimates similar to those derived from live trapping, but a higher density of sampling plots was required for NGS. The optimal NGS protocol for our study entailed deploying 160 sampling plots for 4 days and genotyping one pellet per plot. NGS laboratory costs ranged from approximately $670 to $3000 USD per field site. While live trapping does not incur laboratory costs, its field costs can be considerably higher than for NGS, especially when study sites are difficult to access. We conclude that NGS can work for common species, but that it will require field and laboratory pilot testing to develop cost‐effective sampling protocols.     

Estimating Brownian motion dispersal rate, longevity and population density from spatially explicit mark-recapture data on tropical butterflies

1.?We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2.?The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3.?An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4.?We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity.     

cameratrapR: An R package for estimating animal density using camera trapping data

• 1.Camera trapping plays an important role in wildlife surveys, and provides valuable information for estimation of population density. While mark-recapture techniques can estimate population density for species that can be individually recognized or marked, there are no robust methods to estimate density of species that cannot be individually identified.
• 2.We developed a new approach to estimate population density based on the simulation of individual movement within the camera grid. Simulated animals followed a correlated random walk with the movement parameters of segment length, angular deflection, movement distance and home-range size derived from empirical movement paths. Movement was simulated under a series of population densities. We used the Random Forest algorithm to determine the population density with the highest likelihood of matching the camera trap data. We developed an R package, cameratrapR, to conduct simulations and estimate population density.
• 3.Compared with line transect surveys and the random encounter model, cameratrapR provides more reliable estimates of wildlife density with narrower confidence intervals. Functions are provided to visualize movement paths, derive movement parameters, and plot camera trapping results.
• 4.The package allows researchers to estimate population sizes/densities of animals that cannot be individually identified and cameras are deployed in a grid pattern.

     

Trap Array Configuration Influences Estimates and Precision of Black Bear Density and Abundance

Spatial capture-recapture (SCR) models have advanced our ability to estimate population density for wide ranging animals by explicitly incorporating individual movement. Though these models are more robust to various spatial sampling designs, few studies have empirically tested different large-scale trap configurations using SCR models. We investigated how extent of trap coverage and trap spacing affects precision and accuracy of SCR parameters, implementing models using the R package secr. We tested two trapping scenarios, one spatially extensive and one intensive, using black bear (Ursus americanus) DNA data from hair snare arrays in south-central Missouri, USA. We also examined the influence that adding a second, lower barbed-wire strand to snares had on quantity and spatial distribution of detections. We simulated trapping data to test bias in density estimates of each configuration under a range of density and detection parameter values. Field data showed that using multiple arrays with intensive snare coverage produced more detections of more individuals than extensive coverage. Consequently, density and detection parameters were more precise for the intensive design. Density was estimated as 1.7 bears per 100 km² and was 5.5 times greater than that under extensive sampling. Abundance was 279 (95% CI = 193–406) bears in the 16,812 km² study area. Excluding detections from the lower strand resulted in the loss of 35 detections, 14 unique bears, and the largest recorded movement between snares. All simulations showed low bias for density under both configurations. Results demonstrated that in low density populations with non-uniform distribution of population density, optimizing the tradeoff among snare spacing, coverage, and sample size is of critical importance to estimating parameters with high precision and accuracy. With limited resources, allocating available traps to multiple arrays with intensive trap spacing increased the amount of information needed to inform parameters with high precision.     

Studies on the effects of bait and sampling intensity on trapping and estimating Wood mice, Apodemus sylvaticus

The effects of baiting a Longworth trap with whole oats and the density of traps on an area, or sampling intensity, on trapping and estimating Wood mice were studied on two neighbouring woodland plots in November 1971. Standard capture-mark-recapture (CMR) methods were used for two weeks followed by five nights of removal trapping.
The presence of bait significantly increased the likelihood of capturing marked and unmarked animals. By increasing the sampling intensity a greater proportion of the population was sampled, although the number of animals captured per trap night decreased. These results have been related to the "effective" number of traps on an area.
Observations on population structure, weather, movement and capturing marked and unmarked animals have been made. CMR population estimates closely resembled the cumulative number of individuals captured in each study and were for the main part lower than the estimates from the removal trapping carried out at the end of the studies.     

Inter‐tree distribution of the spruce web‐spinning sawfly,Cephalcia abietis,at endemic density

1 The spatial distribution of forest defoliating insects at endemic density is a generally little known aspect of pest biology, which may have some importance in monitoring and prediction of outbreaks. In a natural spruce stand in Northern Italy it was possible to detect the presence of some species of web‐spinning sawflies (Cephalcia spp.) at endemic density. This was done over a 3‐year period by using trapping devices for both adults and larvae, including a trap which intercepted adult females climbing the trunk. Traps were operated on eight sample trees with signs of defoliation of the previous year (focal trees) and on 14 trees lacking signs of larval feeding (neighbour trees). 2 Trunk traps on focal trees caught a higher number of adult females than traps on neighbour trees in each of the 3 years considered. The distribution pattern of catches was not spatially autocorrelated at any of the distance bands considered. Focal trees produced more mature larvae per adult female of C. abietis than neighbour trees, indicating that insect performance was higher on focal trees. 3 The endemic population density of C. abietis was similar to that observed in other forests and the relationships between yellow trap catches and prepupal density fitted adequately with the predictive model validated for C. arvensis. The endemic density of the spruce web‐spinning sawflies seems to he higher than that of pine diprionids, and outbreak‐prone species of Cephalcia seem to be more abundant than non‐outbreak species even at very low population level.     

A novel approach to the assessment of fruit damage caused by <Emphasis Type="Italic">Carposina sasakii</Emphasis> (Lepidoptera: Carposinidae) using pheromone trap catches in Korean orchards

This study reports a model that utilizes pheromone trap catches to assess the fruit damage caused by Carposina sasakii. The model consisted of four steps: (1) obtaining influx population density using pheromone traps, (2) estimating the actual female population within a defined area using an estimated conversion rate, (3) calculating the total number of eggs using the oviposition model of C. sasakii, and (4) estimating the proportion of fruits infested with eggs (potential damaged fruits) using the relationship between mean egg density per fruit and the proportion of fruits infested with eggs. The relationship between mean egg density ([`(x)] \bar{x} ) per fruit and variance (s ²) was well described by Taylor’s power law, and its parameters were successfully incorporated into the equation that estimates the relationship between mean egg density and the proportion of fruits infested with eggs. In peach orchards, the model accurately predicted the proportion of fruits infested with eggs at the beginning of C. sasakii emergence in early season, but overestimated it in the mid-season. The fitting ability of the model outputs largely increased when the factor of oviposition behavior of C. sasakii was incorporated into the simulation processes, applying the allocation module of total eggs between peaches and apples.     

Trapping Elusive Cats: Using Intensive Camera Trapping to Estimate the Density of a Rare African Felid

Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus) numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9) cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100km²). While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200), no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration) is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.